Nowadays, with the rapid development of Internet finance, new Internet products in the field of finance emerge in endlessly. In order to make the products meet users' demands of function, performance and the like, developers tend to have to deploy applications on a complex system containing a plurality of servers. Meanwhile, software such as an operating system, a middleware and a database should be installed on the servers so as to make the application programs run.
In order to ensure the correct and stable running of the complex system, developers have to make a very well-rounded test on the complex system. A general method is to use the same amount of servers (hardware configurations may be different) to set up a set of testing environment, install essential software products such as the operating system, middleware and database on the testing environment, deploy the application programs, perform parameter configurations on these softwares, and then make the well-rounded test on the application programs. After the application programs pass the test, the above series of software is deployed to a production environment and the parameter configuration is performed, thereby ensuring the correct running thereof.
However, during the deployment to the production environment, it is inevitable that some parameters are wrongly configured. The vast majority of parameters in the production environment are required to have to be consistent with those in the testing environment. Once there is inconsistence in these parameters, the application programs maybe not run normally, causing the application programs which have been passed the strict tests in the testing environment to run wrongly in the production environment, even causing production accident(s). However, due to very high requirements on the information system in the field of finance, the tolerance to the production accident is very low. Therefore, there is an urgent need to provide a method for checking parameters, which avoids the inconsistency of the one parameter in the production environment and in the testing environment so as to lower the possibility of the production accident.